Literature DB >> 28917029

Health-related quality of life and its determinants in patients with metastatic renal cell carcinoma.

S de Groot1,2, W K Redekop3, M M Versteegh3,4, S Sleijfer5, E Oosterwijk6, L A L M Kiemeney6,7, C A Uyl-de Groot3,4.   

Abstract

PURPOSE: Based on improvements of progression-free survival (PFS), new agents for metastatic renal cell carcinoma (mRCC) have been approved. It is assumed that one of the benefits is a delay in health-related quality of life (HRQoL) deterioration as a result of a delay in progression of disease. However, little data are available supporting this relationship. This study aims to provide insight into the most important determinants of HRQoL (including progression of disease) of patients with mRCC.
METHODS: A patient registry (PERCEPTION) was created to evaluate treatment of patients with (m)RCC in the Netherlands. HRQoL was measured, using the EORTC QLQ-C30 and EQ-5D-5L, every 3 months in the first year of participation in the study, and every 6 months in the second year. Participation started as soon as possible following a diagnosis of (m)RCC. Random effects models were used to study associations between HRQoL and patient and disease characteristics, symptoms and treatment.
RESULTS: Eighty-seven patients with mRCC completed 304 questionnaires. The average EORTC QLQ-C30 global health status was 69 (SD, 19) before progression and 61 (SD, 22) after progression of disease. Similarly, the average EQ-5D utility was 0.75 (SD, 0.19) before progression and 0.66 (SD, 0.30) after progression of disease. The presence of fatigue, pain, dyspnoea, and the application of radiotherapy were associated with significantly lower EQ-5D utilities.
CONCLUSIONS: Key drivers for reduced HRQoL in mRCC are disease symptoms. Since symptoms increase with progression of disease, targeted therapies that increase PFS are expected to postpone reductions in HRQoL in mRCC.

Entities:  

Keywords:  Cost-effectiveness analysis; EORTC QLQ-C30; EQ-5D; Health-related quality of life; Metastatic renal cell carcinoma; Targeted therapy

Mesh:

Year:  2017        PMID: 28917029      PMCID: PMC5770482          DOI: 10.1007/s11136-017-1704-4

Source DB:  PubMed          Journal:  Qual Life Res        ISSN: 0962-9343            Impact factor:   4.147


Introduction

Renal cell carcinoma (RCC) accounts for 90% of all kidney cancers [1]. While the prognosis of patients with localised disease treated with surgery is relatively good, the prognosis of patients with advanced or metastatic disease is poor. Median overall survival (OS) ranges from 7.8 months for patients with a poor risk to 43.2 months for patients with a favourable risk according to the Heng criteria [2]. Besides the impact of metastatic renal cell carcinoma (mRCC) on survival, mRCC can be associated with severe symptoms, such as cachexia and/or anorexia, asthenia and/or fatigue, pain, anaemia, and venous thromboembolism [3]. Since 2006, several new targeted therapies have been approved for the treatment of mRCC such as sunitinib, sorafenib, pazopanib and everolimus. In phase III studies, these therapies improved progression-free survival (PFS) of patients with mRCC over the diverse comparators [4-11], but the effect on OS was less pronounced, likely (partly) due to treatment crossover. It is assumed that one of the benefits of the new therapies is a delay in HRQoL deterioration as a result of a delay in progression of disease. Clinicians feel that a better PFS translates into a better HRQoL [12], but little data are available supporting this relationship. In the context of the high prices of targeted therapies which form a strain on health care budgets, it is important to establish whether indeed a delay in progression delays HRQoL deterioration. This study is the first to provide insight into the most important determinants of HRQoL (including progression of disease) of patients with mRCC using data from a patient registry in the Netherlands [13]. Additionally, this study aims to assess if the association between progression and HRQoL, if one exists, is also captured by measures used in economic evaluations to assess benefit (i.e. EQ-5D).

Patients and methods

Study population

A patient registry (i.e. PERCEPTION) was created to evaluate treatment of patients with (m)RCC in the Netherlands. Patients with RCC (all stages) of any histological subtype diagnosed from 2011 until June 30th 2013 in 25 of 32 hospitals (both general and academic) in three regions in the Netherlands were invited to participate, and fill out HRQoL questionnaires. Eligible patients were identified through the hospitals’ registration systems. Additionally, the Netherlands Cancer Registry (NCR), which maintains a cancer registration database of all cancer patients in the Netherlands, was used to ensure that no patients were missed. The research protocol was approved by the medical ethics committee of Radboud university medical center in Nijmegen (CMO Region Arnhem-Nijmegen) in May 2010. Informed consent was obtained from all patients participating in the HRQoL study.

Data collection

Cancer-specific HRQoL was measured using the EORTC (European Organisation for Research and Treatment of Cancer) QLQ-C30 questionnaire (v3.0) [14]. This measure includes five functional scales (physical, role, emotional, social and cognitive), three symptom scales (fatigue, nausea & vomiting and pain), a global health status/QOL scale and six single items (dyspnoea, insomnia, appetite loss, constipation, diarrhoea and financial difficulties). In addition to the EORTC QLQ-C30, the EQ-5D-5L was used to measure HRQoL. The EQ-5D-5L is a preference-based generic measure, and measures HRQoL on five dimensions, i.e. mobility, self-care, usual activities, pain/discomfort and anxiety/depression. Each dimension includes five severity levels [15]. Patients were sent a HRQoL questionnaire every 3 months in the first year of participation in the study, and every 6 months in the second year. Participation started as soon as possible following a diagnosis of (m)RCC. In addition to data on HRQoL, data on demographics, clinical and laboratory factors (to determine the patient’s risk group [16]) were collected retrospectively from individual patient records using uniform case report forms. Furthermore, data on treatment schemes and treatment endpoints (e.g. survival) were derived from patient records. Data collection stopped at the end of 2013.

Statistical analyses

For each scale of the EORTC QLQ-C30, the average of the items that contributed to that scale was calculated. They were then linearly transformed in line with the EORTC QLQ-C30 scoring manual [17]. EQ-5D utilities were derived by combining the answers to the EQ-5D-5L with the Dutch EQ-5D- 5L tariff [18]. Mean EQ-5D utilities and HRQoL based on the EORTC QLQ-C30 were calculated by taking the average of the observations for each patient. The proportion of reported problems for each EQ-5D dimension were presented by taking the modus (i.e. the level reported most frequently) across observations for each patient. If two or more modes exist, the highest level was taken. HRQoL was evaluated separately for the periods before and after progression of disease. In the period before progression of disease, a further distinction was made between wait-and-see and treatment with (first-line) targeted therapy. Treatment was assumed to last until progression of disease. Response including progression of disease was defined based on RECIST (as mentioned in the radiology report). As a substitute (if unavailable) data managers were instructed to register the response as indicated by the physician in the medical record. Patients who did not start therapy within the follow-up period were assumed to wait for therapy during the entire follow-up. Since data on HRQoL were clustered, random effects models [19] were used to study associations between HRQoL (i.e. EORTC QLQ-C30 global health status and EQ-5D utility) and patient and disease characteristics, symptoms and treatment. Use of random effects models ensured that multiple measurements from the same patient were analysed appropriately and made it possible to distinguish between intraindividual and interindividual variation. Backward selection was used to select the covariates for the models; any non-significant covariates were excluded from the models one at a time (significance level of 0.20 for entering and 0.10 for removing the explanatory variables). To control for heteroscedasticity, random effects models with robust standard errors were estimated. Additionally, random effects logit models [19] were used to study associations between the individual EQ-5D dimensions and patient and disease characteristics, symptoms and treatment. EQ-5D levels were dichotomised into ‘no problems/(i.e. level 1) and ‘problems’ (i.e. levels 2–5). Missing data regarding patient and disease characteristics were handled using multiple imputations by chained equations. This method generated imputations based on a set of imputation models, one for each variable with missing values [20]. The significance level was set at α = 0.10. Data analyses were conducted using STATA statistical analysis software (StataCorp. 2013. Stata Statistical Software: Release 13. College Station, TX: StataCorp LP).

Results

Four hundred eleven (m)RCC patients participating in the study completed 1630 questionnaires. The median number of questionnaires per patient was four (range 1–7). The number of questionnaires collected at each time point is provided in the Supplementary material (Fig. S1), as are the number of questionnaires per patient (Fig. S2). The average EORTC QLQ-C30 global health status of patients diagnosed with localised disease (336 patients, 1326 questionnaires) was 76 (SD, 15), and the average EQ-5D utility was 0.82 (SD, 0.17). Eighty-seven patients had mRCC (i.e. metastatic disease at initial presentation or after an initial diagnosis with localised disease). Of these patients, eighty-two percent were male, and the median age at diagnosis was 63 years (Table 1). Twenty-six percent of the population did not receive any systemic therapy during follow-up. Of the patients receiving systemic therapy, the majority (80%) was treated with first-line sunitinib. Twenty-three patients also received a second-line therapy within the follow-up period; the majority of these patients was treated with everolimus (13/23). Thirty-one patients received radiotherapy during follow-up.
Table 1

Baseline characteristics at diagnosis

VariablePatients (n = 87)
Male sex, n (%)71 (82)
Age, median (range)63 (40–79)
Non-clear cell pathology, n (%)17 (20)
WHO performance status, n (%)
 0–182 (94)
 2–45 (6)
More than one metastatic site, n (%)48 (55)
Liver metastasis, n (%)15 (17)
Lung metastasis, n (%)48 (56)
Bone metastasis, n (%)21 (24)
Brain metastasis, n (%)3 (3)
Haemoglobin < LLN, n (%)46 (52)
Neutrophil count > ULN, n (%)18 (21)
Platelet count > ULN, n (%)19 (22)
Corrected serum calcium > ULN, n (%)26 (30)
Lactate dehydrogenase >1.5 times ULN, n (%)11 (12)
Time since RCC diagnosis <1 year78 (90)
MSKCC risk score, n (%)
 Favourable6 (7)
 Intermediate54 (62)
 Poor27 (31)

LLN lower limit of normal, ULN upper limit of normal, RCC renal cell carcinoma, MSKCC Memorial Sloan Kettering Cancer Center

Baseline characteristics at diagnosis LLN lower limit of normal, ULN upper limit of normal, RCC renal cell carcinoma, MSKCC Memorial Sloan Kettering Cancer Center In total, 304 questionnaires were completed by patients with mRCC and the median number of questionnaires per patient was three (range 1–7). Table 2 shows HRQoL during the different stages of the disease. The mean EORTC QLQ-C30 global health status was 67 (SD, 19). Patients primarily experienced problems with role functioning (i.e. doing daily activities and pursuing leisure time activities). Problems with emotional (i.e. feeling tense, irritable, depressed or worrying) and cognitive functioning (i.e. concentrating and remembering) were experienced less often. Symptoms most commonly reported were fatigue, pain, insomnia and dyspnoea. A statistically significant difference was found between the EORTC QLQ-C30 global health status before and after progression of disease, i.e. 69 (SD, 19) and 61 (SD, 22) (p = 0.022). All functioning scales significantly decreased, except for emotional and cognitive functioning. Two symptom scales significantly increased; patients reported more problems regarding dyspnoea (p = 0.031) and diarrhoea (p = 0.057) after progression than before progression of disease.
Table 2

Health-related quality of life based on the EQ-5D and QLQ-C30

Total n = 87 patients (304 obs.)Before progression n = 81 patients (246 obs.)After progression n = 27 patients (58 obs.)
Mean (SD)Total mean (SD)No systemic therapy n = 47 (125 obs.*)Mean (SD)First-line therapy n = 50 (119 obs.)Mean (SD)Total mean (SD)
EQ-5D
 Utility0.74 (0.19)0.75 (0.19)0.76 (0.21)0.76 (0.18)0.66 (0.30)**
EORTC QLQ-C30
 Global health status67 (19)69 (19)69 (22)70 (17)61 (22)***
Functioning scales
 Physical functioning69 (23)71 (23)73 (22)69 (23)62 (29)
 Role functioning59 (28)61 (29)61 (30)62 (29)52 (33)
 Emotional functioning79 (16)80 (18)77 (19)82 (19)73 (19)
 Cognitive functioning80 (20)80 (22)81 (21)79 (25)76 (22)
 Social functioning76 (22)78 (22)77 (20)78 (22)67 (28)
Symptom scales
 Fatigue41 (25)39 (27)36 (27)41 (27)48 (30)
 Nausea and vomiting12 (17)13 (20)8 (13)17 (24)10 (12)
 Pain29 (24)27 (24)24 (25)29 (26)34 (30)
Single items
 Dyspnoea24 (24)23 (24)23 (25)26 (28)29 (34)
 Sleeping28 (26)26 (27)24 (27)27 (30)35 (31)
 Appetite loss19 (26)18 (25)15 (26)21 (26)22 (32)
 Constipation10 (17)9 (17)12 (24)5 (10)12 (21)
 Diarrhoea20 (26)19 (27)13 (27)23 (28)22 (26)
 Financial difficulties10 (18)9 (18)9 (21)11 (19)8 (21)

Obs observations

*Observations of patients who died within 90 days after being diagnosed with mRCC were excluded from this subgroup (n = 2), since these measurements would not contribute to the estimation of the HRQoL of a patient awaiting therapy

**Mean EQ-5D utility of these patients before progression of disease (n = 21) was 0.76 (0.23)

***Mean EORTC QLQ-C30 global health status of these patients before progression of disease (n = 21) was 69 (20)

Health-related quality of life based on the EQ-5D and QLQ-C30 Obs observations *Observations of patients who died within 90 days after being diagnosed with mRCC were excluded from this subgroup (n = 2), since these measurements would not contribute to the estimation of the HRQoL of a patient awaiting therapy **Mean EQ-5D utility of these patients before progression of disease (n = 21) was 0.76 (0.23) ***Mean EORTC QLQ-C30 global health status of these patients before progression of disease (n = 21) was 69 (20) In the period before progression of disease, a similar HRQoL was found for a period without therapy (i.e. wait-and-see) and a period with therapy; mean EORTC QLQ-C30 global health statuses were 69 (SD, 22) and 70 (SD, 17), respectively. However, in the period before progression of disease, patients experienced fewer problems with emotional functioning during a period with therapy compared to a period without therapy (p = 0.067). Additionally, patients reported fewer problems regarding constipation (p = 0.072), but more problems regarding diarrhoea during a period with therapy compared to a period without therapy (p = 0.005). The average EQ-5D utility was 0.74 (SD, 0.19). As with the EORTC QLQ-C30 global health status, a significant difference was found in EQ-5D utility before progression of disease and after progression of disease; the average EQ-5D utility before progression of disease was 0.75 (SD, 0.19), whereas the average EQ-5D utility after progression of disease was 0.66 (SD, 0.30) (p = 0.032). In the period before progression of disease, no significant difference was found between a period without therapy (i.e. wait-and-see) and a period with therapy; mean utilities were 0.76 (SD, 0.21) and 0.76 (SD, 0.18), respectively. In the Supplementary material, Figs. S3 and S4 provide a summary of mean EORTC QLQ-C30 global health statuses and mean EQ-5D utilities by time. Figures 1 and 2 show the proportions of patients reporting levels 1–5 by EQ-5D dimension, before progression of disease and after progression of disease. Both before and after progression of disease, most problems were reported on the mobility, usual activities and pain/discomfort dimensions.
Fig. 1

Proportion of patients reporting levels 1–5 by dimension, before progression of disease

Fig. 2

Proportion of patients reporting levels 1–5 by dimension, after progression of disease

Proportion of patients reporting levels 1–5 by dimension, before progression of disease Proportion of patients reporting levels 1–5 by dimension, after progression of disease Univariable analyses show several relationships between disease characteristics, symptoms and treatment, and HRQoL (Table 3). Patients with brain metastases and patients with progression of disease reported a lower HRQoL than the other patients. Patients with more than one metastatic site or bone metastases reported a lower EQ-5D utility, a relationship that was not seen in the EORTC QLQ-C30 global health status. Additionally, symptoms (i.e. fatigue, nausea and vomiting, pain, dyspnoea, insomnia, appetite loss, constipation and diarrhoea) were associated with a lower HRQoL. Lastly, patients treated with radiotherapy reported a worse HRQoL than patients not treated with radiotherapy.
Table 3

Associations between HRQoL and patient and disease characteristics, symptoms and treatment

EQ-5D utilityEORTC QLQ-C30 global health status
Univariable analysisMultivariable analysisUnivariable analysisMultivariable analysis
CoefficientSECoefficientSECoefficientSECoefficientSE
Patient characteristics
 Male sex0.0770.069NS2.7485.198NS
 Age (per year)−0.0010.002NS−0.2570.223NS
 WHO performance score
  0–1
  2–4−0.080.072NS−5.9197.304NS
Disease characteristics
 More than one metastatic site−0.068*0.035NS−5.0483.3424.048*2.276
 Presence of liver metastases−0.0270.05NS−3.9924.779NS
 Presence of lung metastases−0.0210.041NS0.4654.074NS
 Presence of bone metastases−0.085**0.04NS−3.393.915NS
 Presence of brain metastases−0.285*0.17NS−21.143*10.239−13.586***2.438
 MSKCC risk score
  Favourable
  Intermediate0.0150.062NS−0.4318.924NS
  Poor0.0540.063NS2.4859.22NS
 Progression of disease−0.082**0.036NS−6.897*3−3.859*2.249
 Disease duration (in months)−0.0020.001NS−0.0810.117NS
Symptoms
 Fatigue−0.004***0.001−0.003***0.001−0.451***0.035−0.316***0.042
 Nausea and vomiting−0.001*0.0010.001**0.001−0.360***0.05NS
 Pain−0.004***0−0.002***0−0.324***0.036−0.143***0.035
 Dyspnoea−0.003***0−0.001***0−0.222***0.04NS
 Sleeping−0.002***0NS−0.219***0.035NS
 Appetite loss−0.002***0NS−0.274***0.034−0.111***0.035
 Constipation−0.002***0.001NS−0.186***0.054NS
 Diarrhoea−0.001*0NS−0.089**0.04NS
Treatment
 Systemic therapy versus no systemic therapy0.0260.027NS−0.4872.408NS
 Radiotherapy−0.150***0.042−0.115***0.036−10.017***3.306NS
Model intercept0.943***0.01685.380***1.903
R2 (overall)0.5590.534
Wald test (p value)<0.001<0.001

Several comorbidities at diagnosis were considered for inclusion in the multivariable analyses, but all appeared to be not significantly associated with HRQoL

SE standard error, NS not significant

*Significant at α = 0.1

**Significant at α = 0.05

***Significant at α = 0.01

Associations between HRQoL and patient and disease characteristics, symptoms and treatment Several comorbidities at diagnosis were considered for inclusion in the multivariable analyses, but all appeared to be not significantly associated with HRQoL SE standard error, NS not significant *Significant at α = 0.1 **Significant at α = 0.05 ***Significant at α = 0.01 Multivariable analysis showed that the EORTC QLQ-C30 global health status decreased with the presence of fatigue, pain and appetite loss. Furthermore, the presence of brain metastases and progression of disease were associated with a worse EORTC QLQ-C30 global health status. A similar association was found between fatigue and pain, and the EQ-5D utility. Furthermore, EQ-5D utility scores decreased with the presence of dyspnoea and treatment with radiotherapy. Although the univariable analyses showed several relationships between disease characteristics (e.g. the presence of bone or brain metastases and progression of disease) and HRQoL, these characteristics were no longer associated with a deterioration of HRQoL in multivariable analyses after correction for symptoms (at a significance level of 0.05 and 0.01, except for the presence of brain metastases in the model with the EORTC QLQ-C30 global health status as the dependent variable). This seems to imply that symptoms might increase due to progression of disease (and/or due to the spread of the cancer to the bone or brain), which explains the reduced HRQoL. Table 4 shows that fatigue was associated with all EQ-5D dimensions, except with the mobility dimension; fatigue was associated with a greater frequency of problems regarding self-care, usual activities, pain/discomfort and anxiety/depression. Patients having pain reported problems with all EQ-5D dimensions more often, with the exception of anxiety/depression.
Table 4

Associations between the EQ-5D dimensions and patient and disease characteristics, symptoms and treatment

MobilitySelf-careUsual activitiesPain/discomfortAnxiety/depression
ORSEORSEORSEORSEORSE
Patient characteristics
 Male sex0.149**0.112NS0.095**0.110NSNS
 Age (per year)1.078**0.032NSNSNSNS
Disease characteristics
 Presence of liver metastases4.427*3.395NSNSNSNS
 Presence of lung metastasesNSNSNSNS0.300*0.191
 Presence of bone metastases4.733**2.961NS15.054***14.768NSNS
 MSKCC risk score
  Favourable
  IntermediateNSNSNS0.041***0.049NS
  PoorNSNSNS0.1430.176NS
 Disease durationNS1.073**0.033NSNSNS
Symptoms
 FatigueNS1.044***0.0121.128***0.0281.034***0.0121.021**0.010
 Nausea and vomiting0.967**0.015NSNSNSNS
 Pain1.029***0.0091.030***0.0101.029*0.0151.143***0.023NS
 Dyspnoea1.025***0.009NS1.024*0.014NSNS
 SleepingNSNSNSNS1.016*0.009
 Appetite loss1.031***0.011NSNSNSNS
Treatment
 RadiotherapyNS6.062***3.971NSNSNS

Odds ratios based on models created using multivariable logistic regression

OR odds ratio, SE standard error

*Significant at α = 0.1

**Significant at α = 0.05

***Significant at α = 0.01

Associations between the EQ-5D dimensions and patient and disease characteristics, symptoms and treatment Odds ratios based on models created using multivariable logistic regression OR odds ratio, SE standard error *Significant at α = 0.1 **Significant at α = 0.05 ***Significant at α = 0.01

Discussion

In this study differences were found between the health-related quality of life (HRQoL) of patients with metastatic renal cell carcinoma (mRCC) before and after progression of disease, with a reduced HRQoL after progression of disease. Progression of disease was no longer associated with a deterioration of HRQoL in multivariable analyses after correction for symptoms (at a significance level of 0.05 and 0.01). In line with Wilson and Cleary [21], a relationship between disease characteristics and symptoms was expected, which could explain why disease characteristics (such as progression) were no longer statistically significant in the multivariable analyses. Similarly, bone metastases were no longer associated with a deterioration of HRQoL in multivariable analyses. Since bone metastases can cause pain, then it is not surprising that bone metastases are not significantly associated with HRQoL once pain is included in the analysis. This seems to imply that symptoms increase due to progression of disease (and/or due to the spread of the cancer to the bone), which explains the reduced HRQoL. Besides the relationship between symptoms and HRQoL, a significant association was found between radiotherapy and HRQoL (in the model with the EQ-5D utility as the dependent variable). It is possible that this observed association is not due to radiotherapy itself, but to the selection of which mRCC patients are to receive radiotherapy. That is, radiotherapy is mostly reserved for palliation of local and symptomatic disease or to prevent the progression of metastatic disease in critical sites (i.e. bones and brain) [22]. Either way, radiotherapy appears to be a significant determinant of HRQoL, even after correction for patient and disease characteristics (including bone and brain metastases) and symptoms. The average EQ-5D utility of patients with mRCC was 0.74 compared to an average of 0.84 (SD, 0.18) in the Dutch population aged 60 to 69 [18]. Most patients (74%) in the study population were treated with a targeted therapy (the majority received sunitinib). The average EQ-5D utility of these patients was 0.76 before progression of disease. In a study by Cella et al., a similar EQ-5D utility was reported for patients treated with sunitinib (i.e. 0.75) [23]. In the economic evaluation of bevacizumab and sunitinib by Thompson-Coon and colleagues [24], a health state utility of 0.78 (95% CI 0.76–0.80) was used for progression-free survival and 0.70 (95% CI 0.66–0.74) for progressive disease. These utilities were derived from the data presented in the sunitinib submission to NICE and are somewhat higher than the utilities that we found in our study. The economic evaluation of sunitinib by Remák and colleagues [25] was based on the results of a phase II trial of sunitinib as second-line treatment in mRCC [26]; utilities of 0.72 and 0.76 were used for progression-free survival (i.e. during treatment or rest, respectively), whereas utilities of 0.63 and 0.55 were used for progressive disease (i.e. during second-line treatment or after termination of second-line treatment, respectively). The latter utilities are below the utilities found in our study, but this might be explained by differences in the study population, e.g. patients with progression on first-line cytokine therapy were enrolled in the phase II trial. This study has several limitations that deserve mentioning. First, only 9% of the population (including those patients with RCC but not having metastatic disease) completed the 2-year follow-up period and filled in seven questionnaires. This is mainly because data collection stopped before many patients could be followed up for 2 years after diagnosis. That is, data collection stopped at the end of 2013, which meant that patients diagnosed after January 1st 2012 were not able to complete the full follow-up period. There are no reasons to expect important differences between the patients who did and did not complete the 2-year follow-up. Second, a significant association between WHO performance status and HRQoL, and the MSKCC risk score and HRQoL was not found, although such a relationship would have been expected. The MSKCC risk score divides patients into three risk groups, and gives an indication of the life expectancy of patients with mRCC [16]. Whereas HRQoL was measured several times during the follow-up period, data on patient characteristics (e.g. WHO performance status) and disease characteristics (e.g. laboratory factors, which are part of the MSKCC risk score) were collected once before the start of each new treatment. As a consequence, too few observations on patient and disease characteristics might have been available to detect a significant association between WHO performance status and the MSKCC risk score, and HRQoL. Similarly, a significant association between comorbidities and HRQOL might have been expected, but data on comorbidities were only collected once (at diagnosis) which might explain why a significant association was not found. Nevertheless, the impact of comorbidities on HRQoL might be captured to some extent through age. Age appeared not to be significantly associated with HRQoL. A third limitation is that our study sample was too small to find any difference in EQ-5D utilities between different types of targeted therapies, while these therapies differ in toxicity profiles [27]. Nevertheless, although adverse events have a high impact on HRQoL, an association between adverse events and HRQoL would not be found if the proportion of patients with grade 3 or 4 adverse events is relatively low. Hypertension and fatigue are the most commonly reported grade 3 or 4 adverse events in the randomised phase 3 trial of sunitinib [4], but these adverse events occurred in only 8 and 7% of the population. Therefore, a very large sample size is needed to find any difference in EQ-5D utilities between different types of targeted therapies. Additionally, it is unknown whether the improved HRQoL due to prolonged PFS outweighs reductions in HRQoL due to treatment-related adverse events. Importantly, this study did not find differences in HRQoL of patients treated with systemic therapy and patients not treated with systemic therapy, or between periods with or without systemic therapy. However, this study may have been underpowered to find such differences. A fourth limitation is that no data were collected in the PERCEPTION-registry on assistance provided to patients who reported problems on one or more of the functioning scales of the EORTC QLQ-C30, while these patients could have received assistance to relieve their complaints. For example, patients could have received care at home to help with dressing and washing or emotional support by a psychologist or another healthcare professional. As a consequence, the impact of mRCC on HRQoL as presented in Table 2 might be underestimated. Lastly, the total number of patients with mRCC was 233 in the 2011–2013 Cohort of the PERCEPTION-registry [13], while only 87 patients filled in one or more questionnaires about HRQoL. A comparison of the patient and disease characteristics and outcomes (in terms of overall survival) showed that the patients in the current study had a more favourable prognosis than the other patients in the PERCEPTION-registry. The impact on HRQoL as we estimated in this study is expected to be small, since we presented HRQoL associated with different stages of the disease. To conclude, key drivers for reduced HRQoL in mRCC are symptoms of the disease. Since this study showed that symptoms increase with progression of disease, targeted therapies that increase PFS can help to delay loss in HRQoL. This study also showed that the EQ-5D is able to detect changes in HRQoL of patients with mRCC, as it found associations between well-known symptoms of mRCC and EQ-5D utilities. Similar associations were found between these symptoms and the disease-specific EORTC QLQ-C30. Below is the link to the electronic supplementary material. Supplementary material 1 (PDF 213 KB)
  24 in total

1.  Sorafenib in advanced clear-cell renal-cell carcinoma.

Authors:  Bernard Escudier; Tim Eisen; Walter M Stadler; Cezary Szczylik; Stéphane Oudard; Michael Siebels; Sylvie Negrier; Christine Chevreau; Ewa Solska; Apurva A Desai; Frédéric Rolland; Tomasz Demkow; Thomas E Hutson; Martin Gore; Scott Freeman; Brian Schwartz; Minghua Shan; Ronit Simantov; Ronald M Bukowski
Journal:  N Engl J Med       Date:  2007-01-11       Impact factor: 91.245

2.  Sunitinib versus interferon alfa in metastatic renal-cell carcinoma.

Authors:  Robert J Motzer; Thomas E Hutson; Piotr Tomczak; M Dror Michaelson; Ronald M Bukowski; Olivier Rixe; Stéphane Oudard; Sylvie Negrier; Cezary Szczylik; Sindy T Kim; Isan Chen; Paul W Bycott; Charles M Baum; Robert A Figlin
Journal:  N Engl J Med       Date:  2007-01-11       Impact factor: 91.245

3.  Comparative effectiveness of axitinib versus sorafenib in advanced renal cell carcinoma (AXIS): a randomised phase 3 trial.

Authors:  Brian I Rini; Bernard Escudier; Piotr Tomczak; Andrey Kaprin; Cezary Szczylik; Thomas E Hutson; M Dror Michaelson; Vera A Gorbunova; Martin E Gore; Igor G Rusakov; Sylvie Negrier; Yen-Chuan Ou; Daniel Castellano; Ho Yeong Lim; Hirotsugu Uemura; Jamal Tarazi; David Cella; Connie Chen; Brad Rosbrook; Sinil Kim; Robert J Motzer
Journal:  Lancet       Date:  2011-11-04       Impact factor: 79.321

4.  Linking clinical variables with health-related quality of life. A conceptual model of patient outcomes.

Authors:  I B Wilson; P D Cleary
Journal:  JAMA       Date:  1995-01-04       Impact factor: 56.272

5.  External validation and comparison with other models of the International Metastatic Renal-Cell Carcinoma Database Consortium prognostic model: a population-based study.

Authors:  Daniel Y C Heng; Wanling Xie; Meredith M Regan; Lauren C Harshman; Georg A Bjarnason; Ulka N Vaishampayan; Mary Mackenzie; Lori Wood; Frede Donskov; Min-Han Tan; Sun-Young Rha; Neeraj Agarwal; Christian Kollmannsberger; Brian I Rini; Toni K Choueiri
Journal:  Lancet Oncol       Date:  2013-01-09       Impact factor: 41.316

6.  The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology.

Authors:  N K Aaronson; S Ahmedzai; B Bergman; M Bullinger; A Cull; N J Duez; A Filiberti; H Flechtner; S B Fleishman; J C de Haes
Journal:  J Natl Cancer Inst       Date:  1993-03-03       Impact factor: 13.506

7.  Temsirolimus, interferon alfa, or both for advanced renal-cell carcinoma.

Authors:  Gary Hudes; Michael Carducci; Piotr Tomczak; Janice Dutcher; Robert Figlin; Anil Kapoor; Elzbieta Staroslawska; Jeffrey Sosman; David McDermott; István Bodrogi; Zoran Kovacevic; Vladimir Lesovoy; Ingo G H Schmidt-Wolf; Olga Barbarash; Erhan Gokmen; Timothy O'Toole; Stephanie Lustgarten; Laurence Moore; Robert J Motzer
Journal:  N Engl J Med       Date:  2007-05-31       Impact factor: 91.245

8.  Economic evaluation of sunitinib malate for the first-line treatment of metastatic renal cell carcinoma.

Authors:  Edit Remák; Claudie Charbonneau; Sylvie Négrier; Sindy T Kim; Robert J Motzer
Journal:  J Clin Oncol       Date:  2008-08-20       Impact factor: 44.544

9.  Health-related quality of life in patients with metastatic renal cell carcinoma treated with sunitinib vs interferon-alpha in a phase III trial: final results and geographical analysis.

Authors:  D Cella; M D Michaelson; A G Bushmakin; J C Cappelleri; C Charbonneau; S T Kim; J Z Li; R J Motzer
Journal:  Br J Cancer       Date:  2010-01-26       Impact factor: 7.640

10.  Variation in use of targeted therapies for metastatic renal cell carcinoma: Results from a Dutch population-based registry.

Authors:  S De Groot; S Sleijfer; W K Redekop; E Oosterwijk; J B A G Haanen; L A L M Kiemeney; C A Uyl-de Groot
Journal:  BMC Cancer       Date:  2016-06-11       Impact factor: 4.430

View more
  11 in total

1.  First-line treatments for advanced renal-cell carcinoma with immune checkpoint inhibitors: systematic review, network meta-analysis and cost-effectiveness analysis.

Authors:  Yingjie Su; Jie Fu; Jiangyang Du; Bin Wu
Journal:  Ther Adv Med Oncol       Date:  2020-08-17       Impact factor: 8.168

2.  Diagnostic Workup for Patients with Solid Renal Masses: A Cost-Effectiveness Analysis.

Authors:  Jasmin Runtemund; Johannes Rübenthaler; Niklas von Münchhausen; Maria Ingenerf; Freba Grawe; Gloria Biechele; Felix Gerhard Gassert; Fabian Tollens; Johann Rink; Sasa Cecatka; Christine Schmid-Tannwald; Matthias F Froelich; Dirk-André Clevert; Moritz L Schnitzer
Journal:  Cancers (Basel)       Date:  2022-04-29       Impact factor: 6.575

3.  Comparing the Relative Importance of Attributes of Metastatic Renal Cell Carcinoma Treatments to Patients and Physicians in the United States: A Discrete-Choice Experiment.

Authors:  Juan Marcos González; Justin Doan; David J Gebben; Marco Boeri; Mayer Fishman
Journal:  Pharmacoeconomics       Date:  2018-08       Impact factor: 4.981

4.  First-line Nivolumab Plus Ipilimumab vs Sunitinib for Metastatic Renal Cell Carcinoma: A Cost-effectiveness Analysis.

Authors:  XiaoMin Wan; YuCong Zhang; ChongQing Tan; XiaoHui Zeng; LiuBao Peng
Journal:  JAMA Oncol       Date:  2019-04-01       Impact factor: 31.777

5.  Cost-Effectiveness of Nivolumab Plus Cabozantinib Versus Sunitinib as a First-Line Treatment for Advanced Renal Cell Carcinoma in the United States.

Authors:  SiNi Li; JianHe Li; LiuBao Peng; YaMin Li; XiaoMin Wan
Journal:  Front Pharmacol       Date:  2021-12-13       Impact factor: 5.810

6.  Systematic review and cost-effectiveness of pharmacokinetically guided sunitinib individualized treatment for patients with metastatic renal cell carcinoma.

Authors:  Tingting Chen; Jiahe Chen; Chaoxin Chen; Jianming Guo; Xin He; Song Zheng; Maobai Liu; Bin Zheng
Journal:  Ther Adv Med Oncol       Date:  2022-03-30       Impact factor: 8.168

7.  Cost-Effectiveness of Pembrolizumab plus Axitinib Versus Sunitinib as First-Line Therapy in Advanced Renal Cell Carcinoma in the U.S.

Authors:  Dong Ding; Huabin Hu; Yin Shi; Longjiang She; Linli Yao; Youwen Zhu; Shan Zeng; Liangfang Shen; Jin Huang
Journal:  Oncologist       Date:  2020-09-28       Impact factor: 5.837

8.  Cost-effectiveness of nivolumab plus ipilimumab as first-line therapy in advanced renal-cell carcinoma.

Authors:  Bin Wu; Qiang Zhang; Jie Sun
Journal:  J Immunother Cancer       Date:  2018-11-20       Impact factor: 13.751

9.  Cost-effectiveness of Pembrolizumab Plus Axitinib Vs Nivolumab Plus Ipilimumab as First-Line Treatment of Advanced Renal Cell Carcinoma in the US.

Authors:  Tina R Watson; Xin Gao; Kerry L Reynolds; Chung Yin Kong
Journal:  JAMA Netw Open       Date:  2020-10-01

10.  Quality-adjusted survival with first-line cabozantinib or sunitinib for advanced renal cell carcinoma in the CABOSUN randomized clinical trial (Alliance).

Authors:  Ronald C Chen; Toni K Choueiri; Marion Feuilly; Jie Meng; Johanna Lister; Florence Marteau; Aaron D Falchook; Michael J Morris; Daniel J George; Darren R Feldman
Journal:  Cancer       Date:  2020-10-06       Impact factor: 6.860

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.